The German Federal Office for Information Security (BSI) has adopted a white paper serving as a guide addressing the explainability of AI in adversarial contexts. The white paper aims to inform the development of reliable assessment procedures and digital consumer protection measures in line with the requirements of the European Union AI Act. The document notes (1) the limitations of Explainable AI (XAI), particularly post-hoc methods used to interpret black box AI models; (2) three challenges, namely the disagreement problem, manipulation risks, and fairwashing; (3) solutions to these problems include standardising explanation methods, employing robust audits such as white-box or outside-the-box access), and developing new manipulation-resistant techniques; and (4) detection strategies, such as outlier analysis and statistical comparisons, to identify inconsistencies and prevent deceptive practices in AI assessments.
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